Automated Neuroaxis (Brain and Spine) Imaging with Iterative Scan Prescriptions, Analysis, Reconstructions, Labeling, Surface Localization and Guided Intervention

ABSTRACT

Automated spine localizing, numbering and autoprescription system enhances correct location of diseased or injured tissue, even allow multi-spectral diagnosis. Externally located this tissue is facilitated by an integrated self adhesive spatial reference and skin marking system that is designed for a variety of modalities to include MRI, CT, SPECT, PET, planar nuclear imaging, radiography, XRT, thermography, optical imaging and 3D space tracking. The device ranges from a point localizer to a more multifunctional and complex grid/phantom system. The specially designed spatial reference(s) is affixed to an adhesive strip with corresponding markings so that after applying the unit to the skin/surface and imaging, the reference can be removed leaving the skin appropriately marked. The localizer itself can also directly adhere to the skin after being detached from the underlying strip. A spine autoprescription process performs image analysis that is able to identify vertebrae and discs even in the presence of abnormalities.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of the U.S. ProvisionalPatent Application Ser. No. 60/552,332, filed 11 Mar. 2004, thedisclosure of which is hereby incorporated by reference in its entirety.

FIELD OF THE INVENTION

The present invention relates, in general, to medical diagnostic imagingdevices that perform scout scans for localization and autoprescription.

BACKGROUND OF THE INVENTION

Diagnostic imaging of the spine of a patient is often useful foridentifying disease or an injury to the spine itself or as a readilylocatable landmark for other tissues. Unfortunately, human error mayoccur due to the variability in the patient population or due to anoversight. The mistake may arise in incorrectly labeling vertebrae anddiscs in a diagnostic image. The mistake may arise in incorrectlyvisually identifying the corresponding vertebrae under the skin beforeperforming a surgical or therapeutic (e.g., radiation) treatment. Themistake may arise in improperly identifying a normal, benign, ormalignant condition because an opportunity is missed to correctlycorrelate information from a plurality of imaging systems (e.g., a typeof tissue may be determined if an MRI and a CT image could be properlycorrelated and analyzed).

With regard to spine prescription, a number of complications exist thatnecessitate having an extensively trained clinician identify the imagedvertebrae. For instance, the quality of the diagnostic image may varydepending on the source and type of imaging modality. The presentedimage volume provided may not include the top and bottom vertebrae.Vertebrae and discs may not be adequately captured in the image due tocongenital defect, disease, injury or surgery. The individual inquestion may have an atypical number of mobile pre-sacral vertebrae,either more or less than 23. Further, the spacing and curvature of theindividual's spine may be rather exceptional.

Even if the vertebrae and discs may be accurately identified in thediagnostic image, it is often helpful to be able to obtain a one-to-onecorrespondence between the readily visible and markable skin/surface andunderlying structures or pathology detectable by a variety of imagingmodalities. This may facilitate clinical correlation, XRT, image guidedbiopsy or surgical exploration, multimodality or interstudy imagefusion, motion correction/compensation, and 3D space tracking.

Current methods, (e.g. bath oil/vitamin E capsules for MRI), haveseveral limitations including single image modality utility requiringcompletely different and sometimes incompatible devices for eachmodality, complicating the procedure and adding potential error insubsequent multimodality integration/fusion. They require a separatestep to mark the skin/surface where the localizer is placed and when ascommonly affixed to the skin by overlying tape, may artifactuallyindent/compress the soft tissue beneath the marker or allow thelocalizer to move, further adding to potential error. Sterile techniqueis often difficult to achieve. Furthermore, it may be impossible todiscriminate point localizers from each other or directly attain surfacecoordinates and measurements with cross sectional imaging techniques. Inregards to the latter, indirect instrument values are subject tosignificant error due to potential InterScan patient motion,nonorthogonal surface contours, and technique related aberrations whichmay not be appreciated as current multipurpose spatial referencephantoms are not designed for simultaneous patient imaging.

The trend is to take and digitally store lots of data on a patient,including MR and CT images. You want to both compare each patient's datato his/her own data, and “pools” of data from other people. Littleproblem: How do you make sense of pictures taken at different times,using different types of machines and different actual machines, for thesame or different people? That's what Dr. Weiss accomplishes with histechniques for the skull: well-characterized fixed reference points. Heproposes something similar for the spine. Nothing “automatic” existstoday and there are no real standards for how to characterize points ofreference on the skull, let alone the spine.

Limited coverage, resolution and contrast of conventional MRI localizerscoupled with a high prevalence of spinal variance make definitivenumbering difficult and may contribute to the risk of spinalintervention at the wrong level. Only 20% of the population exhibit theclassic 7 cervical, 12 thoracic, 5 lumbar, 5 sacral, and 4 coccygealgrouping. For instance, 2-11% of individuals have a cephlad or caudalshift of lumbar-sacral transition, respectively resulting in 23 or 25rather than the typical 24 mobile presacral vertebrae. Numberingdifficulties are often heightened in patients referred for spine MRI.Such patients are more likely than the general population to haveanomalies, acquired pathology, or instrumentation that distorts theappearance of vertebrae and discs. Moreover, these patients are oftenunable to lie still within the magnet for more than a short period oftime due to a high prevalence of back pain and spasms. Resultantintrascan motion confounds image interpretation and interscan motionrenders scan coordinates and positional references unreliable.

While data remains somewhat limited, various authors report anapproximately 2-5% incidence of wrong level approach spinalintervention, with most cases involving the lower lumbar interspaces.Such surgical misadventures may lead to needless pain and suffering, aswell as contribute to accelerating medical malpractice costs. The firstmulti-million dollar jury verdict for such a wrong level approach wasawarded in 2002.

Although several research techniques have been described to automatespine image analysis, to the authors' best knowledge, none hassuccessfully addressed the need for accurate and unambiguous numbering.Computer characterization of a vertebrae or disc is of limited clinicalvalue if that structure can not be accurately identified and named.

Consequently, a significant need exists for an improved approach tolocalizing and autoprescribing through multi-modal quick scans of thebrain and/or spine. Furthermore, there is a need for enhancing personalmedicine with a method of aligning skull and spine images.

Once one image set is autoprescribed, it would be further beneficial tocorrelate with other types of imaging modalities that are alsoautoprescribed. One advantage is that calculations of changes over timefor the same patient may quickly identify injury or disease. Anotheradvantage is that different spectral emissions illicit differentinformation about a tissue. Correlating between a plurality of imagingmodalities, if a common tissue structure can be localized for each, mayenable autodiagnosis as to whether the tissue is normal, benign ormalignant. Consequently, it would be of a further advantage to extendspine autoprescription across multiple sources of diagnostic images.

BRIEF SUMMARY OF THE INVENTION

The present invention addresses these and other problems in the priorart by providing an apparatus and method of localizing a spinal columnof a patient with robust automated labeling of vertebrae across apopulation and across different imaging modalities facilitatingautoprescription and follow-on therapeutic procedures. Thereby, humanerror in incorrectly identifying a vertebrae in an image, and thusmislocating a surgical site, is avoided.

In one aspect of the invention, an apparatus processed a medicaldiagnostic image of a patient's torso by identifying voxels ofappropriate size to be putative spinal structures. Then disc constraintsare applied to identify a long chain of spinal structures that are thenlabeled.

In another aspect of the invention, this processing is in conjunctionwith a localized coil placed on the torso of the patient that providesan external reference correlated to the identification and labeling,enabling accurate insertion or aiming of therapeutic treatments.

By virtue of the foregoing, an entire spine can be effectively surveyedwith sub-millimeter in-plane resolution MRI in less than one minute. Allcervical-thoracic-lumbar vertebrae and discs can be readily identifiedand definitively numbered by visual inspection. Allcervical-thoracic-lumbar vertebrae and discs can be readily identifiedand definitively numbered by semi-automated computer algorithm. Rapidtechnique should facilitate accurate vertebral numbering, improvepatient care, and reduce the risk of surgical misadventure. Coupled withan integrated head and spine array coil, rapid computer automatediterative prescription and analysis of the entire neuro-axis may bepossible.

These and other objects and advantages of the present invention shall bemade apparent from the accompanying drawings and the descriptionthereof.

BRIEF DESCRIPTION OF THE FIGURES

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate embodiments of the invention,and, together with the general description of the invention given above,and the detailed description of the embodiments given below, serve toexplain the principles of the present invention.

FIG. 1 is a diagram of an automated spinal diagnostic system.

FIG. 2 is a flow diagram of a spine identification sequence oroperations or procedure for the automated spinal diagnostic system ofFIG. 1.

FIG. 3 is a diagram of a projection function of adjacent objects (_(p)and (_(q) represent the angles between the line connecting candidatedisc p and q through their centroid and the major axis of disc p and qrespectively, wherein 0<(_(p)<90° and (_(p)<45° and (_(p)<45° let d_(c)be the value of d for any candidate disc in cervical-thoracic spineregion and d_(L) in the thoracic-lumbar spine, then 6 mm<d_(c)<80 mm and8 mm<d_(L)<100 mm.

FIG. 4 is a diagram of distance constraint chains with a cluster, k, ispart of a disc chain if its closest superior neighbor has k as itsclosest inferior neighbor and k's closest inferior neighbor has (k) asits closest superior neighbor.

FIG. 5 is a 7-slice sagittal MRI projected image volume having a 35 cmFOV top half and

FIG. 6 is a 35 cm FOV bottom half illustrating typical search regionswherein voxels exceeding intensity threshold are depicted with thosemeeting additional disc constraints are highlighted as putative disksand connected by a curved line through their centroids.

FIG. 7 is a combined sagittal image depicting search paths parallel tothe curved line of FIG. 6 connecting a centroid of a C2-3 disc withlongest disc chains from top and bottom half images (FIGS.). Dotscorrespond to local maxima along these paths.

FIG. 8 is a sagittal image through the entire spine with allintervetebral discs auto-labeled with labeling of vertebrae omitted forclarity with three-dimensional (3-D) coordinates generated by analgorithm providing a means for discs or vertebral bodies to be labeledin any subsequent imaging plane providing no gross inter-scan patientmovement.

FIG. 9 a sagittal image through the entire spine of a patient with 23mobile/presacral vertebrae with correct auto-labeling of first 22interspaces.

FIG. 10 a sagittal image through the entire spine of a patient with 25potentially mobile presacral vertebrae with correct auto-labeling of thefirst 23 interspaces.

FIG. 11 a sagittal image through the entire spine of a patient withsurgically fused L4-5 interspace and associated artifact from a metalliccage with correct labeling of all 23 interspaces including a goodapproximation of the L4-5 disc.

FIG. 12 a sagittal image through the entire spine of a patient withvertebral planus of T-10 mislabeled due to a less robust discdiscrimination process.

FIG. 13 is a sagittal image through the entire spine of the patient ofFIG. 12 with correctly labeled vertebrae due to a more robust discdiscrimination process including Gaussian filters.

FIGS. 14A-14I are diagrams of a point localizer; FIG. 14A depicts afrontal view of the point localizer affixed to fabric; FIG. 14B depictsa reverse side of the point localizer of FIG. 14A; FIG. 14C is aperspective view of the point localizer and underlying fabric affixed tothe skin; FIG. 14D is an enface view of the fabric with correspondingmarking affixed to the skin; FIG. 14E is an enface view of the localizeraffixed to skin; FIG. 14F is a diagram view of a port integrated into atubular ring; FIG. 14G is a frontal view of a modified ring shapedlocalizer affixed to fabric with additional markings; FIG. 14H is afrontal view of the fabric in FIG. 14G with the localizer removed; FIG.14I is a frontal view of a multilocalizer sheet demonstrating theadhesive backing and overlying fabric with localizers removed.

FIGS. 15A-15F illustrate a cross-shaped grid configuration; FIG. 15A isan enface view of the grid with modified square as the central hub anduniquely positioned rows of tubing radiating along the vertical andhorizontal axes; FIG. 15B is a schematic of axial cross sectionsacquired at representative distances from the horizontal axis; FIG. 5Cdemonstrates the underlying marked fabric with the superimposed tubingin FIG. 15A removed; FIG. 15D is a variant of FIG. 15A with modifiedring serving as a central hub; FIG. 15E depicts a limb fixation ring andangulation adjuster; and FIG. 15F depicts a radiopaque grid withunderlying ruled fabric strips removed.

FIG. 16A is an enface view of the grid/phantom configuration withtubular lattice, overlying a diagonally oriented slice indicator, andunderlying a partially adhesive fabric with markings and perforations;FIG. 16B is a schematic cross section of a representative axial sectionof the grid/phantom configuration of FIG. 16A.

FIGS. 17A-17B are diagrams of localizers in a packaged strip or roll,regularly spaced at 5 cm or other intervals.

FIGS. 18A-18B are a lattice localizer having tube diameters varied toidentify unique locations.

FIGS. 19A-19D are depictions of a fall-spin grid localizer and spinalcoil.

DETAILED DESCRIPTION OF THE INVENTION

Spine Localization, Automated Labeling, and Data Fusion DiagnosticSystem.

In FIG. 1, an automated spinal diagnostic system 10 includes adiagnostic imaging system 12 (e.g., MRI, CT) that is used to image atorso of a patient 14 that is advantageously covered by a skin/surfacemarking system 16 that serves as an integrated multimodality,multi-functional spatial reference. The diagnostic imaging system 12 mayinclude scanning of the skull 18, the full spine 20, and pelvic bones22. The diagnostic imaging system 12 serves as an automated MRItechnique that rapidly surveys the entire spine providing accuratedefinitive numbering of all discs and vertebrae. In the particularillustrative version, the entire spine can be effectively surveyed withsub-millimeter in-plane resolution MRI in less than 1 minute. C-T-Lvertebrae and discs can be readily identified and definitively numberedby visual inspection or semi-automated computer algorithm (“ASSIST”).

Correctly identifying each vertebrae and disc in the spine 20 iscomplicated in certain instances when the skull 18 and/or the pelvicbones 22 are not imaged. In some instances, a vertebrae or disc(depending on whether CT or MRI is being used respectively) will fail toimage properly, depicted at 24. In addition, the highly predominantnumber of twenty-three vertebrae may not be the case for certainindividuals, such as twenty-four as depicted. Having the correctvertebrae references may be important in localizing a suspicious lesion26, such as for a later therapeutic procedure, represented as aradiation device 28.

The diagnostic imaging system 12 may derive a sagittal image 28 of thetorso 14 from a volume CT scan 30. Alternatively, the diagnostic imagingsystem 12 may produce an upper cervical-thoracic sagittal image 32 and alower thoracic-lumbar sagittal image 34, such as from MRI. A spineautoimage processor 40, which may be a process hosted by the diagnosticimaging system 12 or by a remote device, performs a number ofsubprocesses to correctly identify and label the spine 20.

In an illustrative version of the diagnostic imaging system 12, MRIstudies were performed on a clinical 1.5T magnet with standard 4-channelquadrature array 6-element spine coil and surface coil correctionalgorithm. Contiguous two-station 35 cm FOV sagittal FGRE sequences werepre-programmed, providing full cervical, thoracic and lumbar (C-T-L)spine coverage. Combined sagittal FOV of 70 cm., 7 sections, L15-R15, 4mm skip 1 mm; 512×352, 1 nex, TR 58, TE 2.0, 30° flip, BW 15.6; 21 sec×2stations=42 sec. To facilitate and standardize auto-prescriptions, aline was drawn on the spine coil for the technologists to landmark (setas scanner's 0 coordinate) rather than have them use a superficialanatomic feature. The coil has a contoured head/neck rest assuringgrossly similar positioning of the cranial-cervical junction of eachpatient relative to this landmark. The semi-automated disc detection andnumbering algorithm of the spine image processor 40 was iterativelydeveloped, tested and refined on batches of consecutive de-identifiedpatient studies and results compared to neuroradiologist assignments.The spine image processor 40 was implemented in MATLAB 7.

In block 41, a computer algorithm is hosted on the spine image processorfor the identification and labeling of disc and vertebrae fromauto-prescribed sagittal MRI or sagittal auto-reformatted CT data,described in greater detail below. This information may beadvantageously provided to an automated spine image analysis algorithm43 that further characterizes each disc and/or vertebrae level.Alternatively or in addition, this information from block 41 may beadvantageously provided to an auto-prescription algorithm 45 foradditional image sequences, utilizing the identified spinal landmarks asreferences. Further, the additional processes 43, 45 may exchangeinformation with each other, such as detained analysis and diagnosis ofa particular vertebrae in block 43 being enabled by auto-prescribeddetailed images in block 45.

These analyses performed by the spine image processor 40 in theillustrative version key upon one or more sources of information thatidentify the top vertebrae.

In particular, in block 46, a top vertebrae is identified, which may beautomated in block 48 by interfacing with an automated craniumidentification system, such as described in U.S. patent application Ser.No. 10/803,700, “AUTOMATED BRAIN MRI AND CT PRESCRIPTIONS IN TALAIRACHSPACE” to Dr. Weiss, filed 18 Mar. 2004, the disclosure of which ishereby incorporated by reference in its entirety. Alternatively, logicmay be incorporated into the spine image processor 40 wherein a spinealgorithm in block 50 recognizes a top vertebrae. As a furtheralternative and as fall back option should automated means fail, inblock 52 a technologist input is received to identify the top vertebrae.

The neuroradiologist could readily visualize and definitively number allC-T-L levels on ASSIST localizers. 6/50 patients had a congenital shiftin lumbar-sacral transition; 3 with 23 mobile pre-sacral vertebrae and 3with 25 mobile pre-sacral vertebraeBased upon usual of manual placementof a single seed in the C2-3 interspace for accurate identification andnumbering of the other 22 discs, in the illustrative version with 50/50cases performed by the spine autoprescription processor 40. Theautomated disc detection and numbering algorithm was concordant withneuroradiologist assignments in 50/50 (100%) of cases.

With a labeled disc image 64, correct relative location to other imagedtissue of interest, depicted at 65 may be used for further diagnosticprocedures or therapeutic intervention. For instance, in block 66 withan ability to correlate images taken with the same type of imagingmodality at different times, growth progression of a suspicious lesionor changes due to an intervening injury may be compared between images.In addition, images taken with different imaging modalities may be crossreferenced to perform multi-spectral diagnoses (block 68), whereininformation on a type of tissue may be gained by its different responsesto various types of electromagnetic spectra. With tissue diagnosiscomplete, in block 70 may correctly orient a therapeutic agent, such asthe radiation device 28 or a guided minimally invasive surgicalinstrument (not shown). Alternatively, for an externally orientedprocedure, a surgeon may reference either the relative location to aknown spinal constituent (e.g., vertebrae) and/or reference theskin/surfacing marking system 16.

In an illustrative implementation of the spine image processor 40 ofFIG. 1, Internal Review Board (IRB) approval for the research study wasobtained. As part of a revised thoracic spine clinical MRI protocolinstituted at an outpatient imaging facility, patients received a rapidtotal spine ASSIST localizer with pre-set parameters. All studies wereperformed on a 1.5T GE Excite MRI system with standard 4-channel,6-element quadrature spine coil and surface coil correction algorithm.Contiguous two-station 35 cm FOV sagittal FGRE sequences werepre-programmed, providing full cervical, thoracic and lumbar (C-T-L)spine coverage. Combined sagittal FOV was 70 cm., 7 sections obtained ateach station, L15-R15, 4 mm skip 1 mm; 512×352, 1 nex, TR 58, TE 2.0,30° flip, BW 15.6; 21 sec×2 stations=42 sec. These ASSIST studies werede-identified in consecutive batches and copied to CD for subsequentoff-line review, computer algorithm development and testing. Asemi-automated disc detection and numbering algorithm was iterativelydeveloped and results compared to neuroradiologist assignments.

The first batch of 27 cases was initially run with an algorithm 100developed using previously obtained, non surface-coil corrected ASSISTimages, The first step, we input cervicothoracic (top half), andthorariclumbar (bottom half) spines. A threshold and a median spatialfilter are applied to the search region. Then, additional discconstraints are applied to identify longest chain in top and bottomimages. Candidate discs must extend onto at least two adjacent slices.Objects at the boundary or touching the boundary of the search regionare excluded. Different threshold values, and candidate discs'constraints are applied to the top, and bottom half image.

In FIG. 2, the automated disc detection and numbering algorithm 100 is amulti-step iterative process. DICOM (i.e., Digital Imaging andCommunications in Medicine) ASSIST images of the cervicothoracic (tophalf), and thorarolumbar (bottom half) spine are first input into MATLAB7 (The Math Works, Inc., Natick, Mass.) for digital image processing.

Initially, these two data sets are processed to obtain putative discsseparately, utilizing different threshold values and disc constraintparameters (block 104), with resulting upper and lower images 106, 108depicted in FIGS. 5 and 6 respectively. Image volumes 106, 108 areenhanced with a tophat filter and background noise is suppressed. Aposterior edge 110 of the back is then identified in each image 106, 108and search regions 112, 114 assigned respectively. The algorithm 100thresholds and applies a median spatial filter to the search regions.Voxels 116 exceeding threshold values are then subjected to additionalconstraints.

Acceptable voxels 120 must extend onto at least two adjacent sagittalsections but not touch the boundary of the search region 112, 114. Theacceptable voxels 116 must lie 6-80 mm in the cervicothoracic (C-T), and8-100 mm in the thoracolumbar (T-L) region from adjacent candidatevoxels 120. The centroids of these voxel clusters 120 (candidate discs)are then connected by curved line 122. The angle subtended by the line122 connecting the centroid of adjacent candidate discs 120 and themajor axis of these discs 122 must be between 45° and 135° in both theC-T and T-L spine. In FIG. 3, projection analysis is used to constraindisc assignments. Furthermore, for a disc (k) to be considered part of achain, its closest superior neighbor must have k as its closest inferiorneighbor and k's closest inferior neighbor must have k as its closestsuperior neighbor. In FIG. 4, an angle relative to the major axis isevaluated to constrain disc assignments. The algorithm selects thelongest disc chain (white discs connected by curved line) in the C-T andT-L regions respectively (FIGS. 5, 6).

In block 130, the technologist is instructed to approximate (click on)the centroid of C2-3 at anytime during or before the aforementionedcandidate disc evaluation. The centroid of C2-3 and the longest discchains in the C-T and T-L spines are connected with a straight line.Using 3D linear interpolation, the program searches along this line andtwelve adjacent parallel lines 140, represented by only four in FIG. 7for clarity due to their superimposition in the sagittal projection.After applying Gaussian filters, the algorithm 100 finds local intensitymaxima along each path. Points 142 that are less than 7.5 mm apart aregrouped into clusters. These clusters are analyzed based on orientation,eccentricity, and spatial relationship relative to other clusters (block144 of FIG. 4).

Continuing with FIG. 2, if twenty-three (23) discs are selected in block146, the computer auto-labels theses discs or adjacent vertebrae andstops (block 148), as depicted in FIG. 8. Otherwise, search criteria andthresholds are refined based on estimated inter-disc height (h) for eachdisc level (L) using the following formula: (equation 1) h=0.6M for L=1,2, or 3 and h=M+(L−1.2)*0.05M for L>3. where M (mean)=distance alongline thru centroids/23.

In block 150, if 23 discs are not yet identified in block 146, theprogram 100 extends the search line inferiorly based on the estimatedposition (E_(x,y)) of the missing disc(s). $\begin{matrix}{E_{({x_{j},y_{j}})} = {\left( {x_{j - 1},y_{j - 1}} \right) + {{h_{a}\left( {x_{j - 1},y_{j - 1}} \right)} \times {\sum\limits_{1}^{j - 1}\frac{h_{s}\left( {x,y} \right)}{h_{a}\left( {x,y} \right)}}}}} & \left( {{Equation}\quad 2} \right)\end{matrix}$where ∂_(a) is the average vertebral height from a 22 subject trainingset, ∂_(s) is the vertebral height from the subject in question. Theprogram searches for local maxima along this line extension and 24adjacent parallel lines. A further determination is made in block 152 asto whether 23 discs have been found. Iteration continues as long astwenty-three (23) discs are not selected, as represented by block 154that extends the search and the further determination of block 156,which labels the vertebrae is 23 are selected (block 157).

If not 23 discs in block 156, then in block 158 a further determinationis then made that twenty-two (22) discs are selected. If so, thealgorithm 100 will determine in block 160 whether the last identifiedlevel (L4-5) satisfies criteria for the terminal pre-sacral interspacesuggesting a congenital variant with 23 rather than the typical 24mobile presacral vertebrae (block 162). To be considered a terminaldisc, the centroid of the 22nd disc must lie within 25% of its expectedlocation (Ex,y) relative to the 21st disc. Additionally, the centroidmust lie posterior to the centroid of the 21^(st) disc and the slope ofthe 22^(nd) disc must be positive and greater than that of the 21^(st)disc.

If found in block 166, the discs are labeled in block 168. Else, if theterminal disc criteria are not met in block 166, the position of the23^(rd) (L5-S1) disc is estimated using Equation 2 (block 164), andsearch constraints refined. If the 23^(rd) disc is still not identifiedin block 166, the disc is presumed to be severely degenerated orpost-surgical and the estimated position for L5-S1 will be accepted inblock 170 and the discs thus labeled (block 172).

If less than 22 discs are identified by the algorithm in block 158, thenthe technologist will be instructed in block 174 to approximate (clickon) the centroid of the last disc. The “combine data” step from block144 is repeated and if necessary the “search for additional discs” stepas well. If twenty-three (23) discs are selected in block 176, then thediscs are labeled in block 178. Else, if twenty three (23) discs arestill not selected in block 176, the algorithm prints out, “Sorry,computer unable to detect all the discs. Require technologist revision.”(block 180)

The algorithm was run on an INTEL (San Jose, Calif.) personal computerwith a 2.8 Ghz Xeon processor. Computer auto-labeling was compared toindependent neuroradiologist assignments for each patient's study. Theautomated spine MRI sequencing provided a robust survey of the entireC-T-L spine in 42 seconds total acquisition time. In all patients(50/50), the neuroradiologist could readily visualize and definitivelynumber all C-T-L levels on the ASSIST localizers. These included sixpatients with a congenital shift in their lumbar-sacral transition;three with 23 mobile pre-sacral vertebrae (FIG. 5) and three with 25mobile pre-sacral vertebrae (FIG. 6). Several patients hadpost-operative spines to include metallic instrumentation (FIG. 7).

Automated disc detection/numbering: the initial algorithm tested on thefirst 27 surface-coil corrected studies was accurate in 26/27 cases(96%), the single error related to a severely collapsed vertebra (FIG.12). The modified algorithm was accurate in all 50/50 cases (100%) ofthe patients to include the original 27 patients plus 23 subsequentcases, despite the presence of congenital variations (FIGS. 5, 6),post-operative changes (FIG. 11), and prominent disc or vertebralpathology (FIG. 13) in this patient population. None of the 50 casesrequired technologist input of more than a single interspace (C2-3)though the algorithm provides such an iterative pathway if necessary. Inthe vast majority of cases, the algorithm 100, running on a personalcomputer with a 2.8 GHz processor, took less than 2 minutes to identifyand label all intervertebral discs or vertebrae.

Although the ASSIST algorithm 100 was successful in all 50 patientsstudied, the 7 section sagittal acquisition would be expected to fail insubjects with severe scoliosis due to insufficient spine coverage. Assuch, if significant scoliosis is suspected, more sagittal sectionscould be auto-prescribed, the cost being a proportionate increase inscan time. The automated disc detection/numbering algorithm 100 wasdesigned to accept any number of sagittal sections, however, itsaccuracy in patients with severe scoliosis is unknown and parametermodifications might be required. Additionally, ASSIST algorithm 100 wasdesigned and tested only on an adult population. Consequently, thealgorithm would likely require additional testing and modifications toperform optimally in the pediatric population.

While the illustrative disc detection algorithm 100 presently requiresmanual input of the most cephalad disc, C2-3, to achieve maximalaccuracy, it should be appreciated that automated computer detection ofthis interspace may be implemented. The C2-3 disc may be readilydiscerned on midline sagittal head images with a 22-24 cm FOV (Weiss2003, 2004) or ASSIST 35 cm FOV cervico-thoracic spine images based onseveral unique features. These include the characteristic shape of theC2 vertebrae and relatively constant relationship to the skull base andcervico-medullary junction.

Although the illustrative version is described for MRI, it should beappreciated that the ASSIST algorithm 100 has applications to otherimaging platforms, such as CT, substituting automated sagittal CT spinereconstructions for the direct sagittal MRI acquisitions facilitatingautomated temporal comparisons, multi-modal multiparametric spinalanalysis, and optimized intervention. As disclosed for MRI and CT of thebrain in the cross-referenced application, direct scanner integrationand related algorithms for computer assisted diagnosis could eventuallyenable “real-time” automated spine image analysis and iterative scanprescriptions.

For example, optimally angled axial oblique sequencing could beauto-prescribed through all interspaces or those discs demonstratingabnormal morphology or signal characteristics on the ASSIST orsubsequent sagittal sequences. By streamlining and converting Matlabcode to C++, algorithm processing time might be significantly shortened.Coupled with an integrated head and spine array coil, rapid computerautomated iterative prescription and analysis of the entire neuro-axismay be possible.

In conclusion, the entire spine can be effectively surveyed withsub-millimeter in-plane resolution MR in less than 1 minute. All C-T-Lvertebrae and discs can be readily identified and definitively numberedby visual inspection or semi-automated computer algorithm. We advocateASSIST for all thoracic and lumbar spine MRI studies. This rapidtechnique should facilitate accurate vertebral numbering, improvepatient care, and reduce the risk of surgical misadventure.

Integrated Multimodality, Multi-Functional Spatial Reference andSkin/Surface Marking System.

With internal structures labeled, there are a number of advantages toproviding an external skin/surface marking system. There are three majorconfigurations of the device as follows: (1) a point localizer, (2)cross-shaped localizer grid, and (3) full planar localizer grid/phantom.

In one version, the point localizer 500 of FIGS. 14A-14I is amultimodality visible and compatible affixed to an adhesive fabric stripwith corresponding markings so that after application and imaging thelocalizer can be removed with skin marking remaining. The localizer canalso directly adhere to the skin. Alternatively, an ink or dye could beadded to the adhesive/undersurface of the localizer to directlymark/imprint the skin obviating the fabric strip. For MRI and CT a smallloop of tubing could be filled with a radioattenuative solution (e.g.containing iodine) doped with a paramagnetic relaxant (e.g. CuS04,MgS04, Gd-DTPA). Alternatively, the tubing itself may be radiopaque foroptimal CT visualization. For nuclear imaging to include planarscintigraphy, SPECT and PET, a port would be included to allow fillingwith the appropriate radionuclide. While the above localizers would bevisible with planar radiography, a fine wire circle or dot (e.g. lead,aluminum) could be utilized with this modality given its very highspatial resolution. Other shapes and corresponding adhesive markingscould be utilized to discriminate different foci and/or add furtherlocalizing capability. Additionally, an activatable chemiluminescentmixture could be added for thermography, optical imaging, light based 3Dspace tracking or simply improved visualization in a darkenedenvironment.

In the second major configuration, a unique cross shaped grouping ofprefilled or fillable tubing is utilized as a grid for cross sectionalimaging with the number and position of tubes imaged in the axial orsagittal planes corresponding respectively to the slices z or y distancefrom the center. For planar radiography, a flexible radiopaque ruledcross shaped grid is employed. Both grids are removable from similarlyruled cross shaped adhesive strips after patient application andimaging.

Lastly, a unique essentially planar grid/phantom is described which maybe of flexible construction and reversibly affixed to anadhesive/plastic sheet with corresponding grid pattern for skin markingand to serve as a sterile interface between patient and reusablegrid/phantom. The grid/phantom may also be directly adherent to the skinfor guided aspiration or biopsy with the cross sectionally resolvablespatial reference in place. A diagonally oriented prefilled or fillabletube overlies a grid like lattice of regularly spaced tubing so thatslice location and thickness can be readily determined in the axial andsagittal planes. Additionally, the spatial accuracy of the imagingmodality could be assessed and, if individual tubes are filled withdifferent solutions, multipurpose references for MR/CT, and nuclearimaging could be achieved. Furthermore, if the tubing is surrounded by aperflurocarbon or other uniform substance without magneticsusceptibility, MR imaging could be improved by reducing skin/airsusceptibility and motion artifact. Additionally, the grid/phantom couldbe incorporated in routinely utilized pads and binding devices with orwithout skin adhesion and marking.

Returning to the Drawings, FIGS. 14A-14I depict an illustrative versionof a point localizer 500. In FIG. 14A, a loop of prefilled tubing 510(i.e., a tubal lumen shaped into a tubal ring) is shown superimposed onand reversibly affixed to an underlying medical grade fabric 511, whichmay double as an adhesive bandage to both cover and mark a wound orpuncture site. The diameter of the tubular ring 510 may be 2 cm midluminal, as illustrated, or outer luminal, as perhaps preferable forintegration with the cross shaped grid configuration. Other sized rings,to include in particular a 1 cm. diameter, may also have merit. Thetubal lumen should measure 2-5 mm in cross sectional diameter. Crosssectional images through the ring will have characteristic andquantifiable appearances depending on slice thickness and distance fromthe center. A thin slice through the loop's center, for example, woulddemonstrate 2 circles of luminal diameter whose centers are separated bya distance equal to the ring's diameter.

The tube lumen can be filled with an appropriate concentration of aniodinated contrast agent for optimal CT visualization doped with aparamagnetic relaxant such as CuS04,MgS04, or GdDTPA to maximize MRIsignal via preferential T1 shortening. Alternatively, the tubing itselfmay be optimally radiopaque for CT, obviating the iodinated contrast. Ifdesired, for optical imaging, thermography, light based 3D spacetracking, or improved visibility in a darkened environment, one couldadd an activatable chemiluminescent mixture whose critical reagents areseparated by a membrane readily breached by external force applied tothe ring.

A slightly redundant backing 512 is provided for the adhesive side ofthe fabric 51 to facilitate peeling (FIG. 14B arrows) and skinplacement. With backing 512 removed, the unit 500 adheres to skin 513 asdepicted in FIG. 14C. After imaging, the loop 510, which has its ownadhesive undersurface, may be removed revealing an underlying fabricmarking 514 as in FIG. 14D. The upper surface of the fabric, orcircumscribed area thereof, may also have adhesive backing-likeproperties to facilitate detachment of the ring 510. Once separated fromthe fabric, the loop 510 could also directly adhere to the skin 513 asin FIG. 14E. Additionally, the adhesive undersurface of the ring couldcontain a medical grade dye or ink so that a corresponding imprint wouldbe left on the skin 513 after removal, potentially obviating the fabricmarker.

A port 515 may be directly integrated into the tubular ring 510 as inFIG. 14F, and a vacuum created within the lumen to facilitate filling atthe imaging center. This feature would be critical for radionuclidescans and add flexibility for other imaging studies.

To increase spatial reference capability and allow multiple localizersto be discriminated from each other, the ring and underlying fabricmarking may be modified as in FIGS. 14G and 14H. As illustrated, twotubular spokes 516 at right angles to each other may be added withluminal diameter less than or equal to that of the loop. Typically, themodified ring would be positioned on the patient so that the spokes arealigned at 0 and 90 degrees as perhaps determined by the scanner'salignment light. Subsequent rings could be progressively rotated 90degrees so that quadrants I, II, III, and IV are sequentially subservedby the spokes. With the simple ring included, this would provide 5distinguishable localizers. Moreover, if stacking of two rings isutilized, 30 (5×6) distinguishable localizer configurations arepossible. Suggested numbering would employ the base 5 system, assigningthe simple ring the value 0 and each modified ring the value of thequadrant subserved.

Multiple localizers may also be dispensed on a single sheet rather thanindividually packaged. FIG. 14I illustrates such a sheet, demonstratingadhesive backing 517 and overlying fabric 511 with the simple ring (leftside) and modified ring (right side) localizers removed. Tabs 518 havebeen added to the fabric to facilitate both removal of the unit from thebacking and the localizer from the fabric. Discontinuity of the backing(solid lines 519) underlying the tabs would also simplify removal of thefabric from—the backing and perforations through the backing (dottedlines 520) would facilitate separation of individual units from eachother. If desired, a smaller diameter (e.g. 1 cm) ring and associatedbacking albeit without tab could be placed within the central space (21)bordered by the simple ring fabric 519.

Embodiments of a prefilled or fillable cross shaped localizer grid 600are illustrated in FIGS. 15A-15F. In FIG. 15A, a modified tubular square621 with diagonal dimensions of 2 cm and containing 2 smaller caliberspokes 623 at right angles to each other serves as the hub. Uniquelypositioned rows of tubing (24) radiate from each corner along thevertical and horizontal axes. The luminal diameter of the radiatingtubes is uniform and on the order of 2 mm. except where indicated bydotted lines 625 corresponding to gradual tapering from 0 to the uniformdiameter. Depending on the distance from the central hub, with 1 or 2rows of tubing will be present with up to 4 tubes in each row as bestillustrated in a table of FIG. 15B. The lower row of tubes (i.e. closestto skin) would correspond to increments of 1 cm. and the upper row toincrements of 5 cm so that a maximum distance of 24 cm would be denotedby 2 full rows. To indicate positive distances, the tubes areprogressively ordered from left to right or down to up with the reversetrue for negative distances as illustrated in FIGS. 15A-15B. Fractionsof a centimeter would be indicated by the diameter of a cross sectionthrough a tapered portion of tubing divided by the fall uniformdiameter.

The cross-shaped grid of tubing is reversibly affixed to a medical gradeadhesive fabric 626 with corresponding markings and backing. The fabric626 is illustrated in FIG. 15C with the overlying tubing removed. Thegrid and associated fabric may come as a single cross-shaped unit or asa modified square and separate limbs which could be applied to thepatient individually or in various combinations. Modified squares couldalso link whole units and/or individual limbs together to expandcoverage, with 25 cm. spacing between the center of adjacent squares.The tubing may be flexible to allow the limbs to conform to curved bodycontours such as the breast. Additionally, either the limbs could bereadily truncated at 5 cm. intervals or be available in various lengthsfor optimal anatomic coverage.

To add further utility and integration with the previously describedpoint localizers, a modified ring may serve as the hub of thecross-shaped grid with associated modification of the limbs asillustrated in FIG. 15D. The orthogonal limbs would not have to maintaina coincident relationship to the spokes as with the modified square hub.Rather, by first placing and rotating a calibrated ring adapter (FIG.15E) about the modified loop, 1 to 4 limbs could be readily positionedat any desired angle relative to the spokes. Pairs of male plugs 627extending from the ring, adapter would fit securely into correspondingholes 628 at each limb base to ensure proper positioning. It is foreseenthat one would typically align the modified ring's spokes with thescanner's axes and the ring adapter/limbs with the axes of the body partto be studied. By noting the chosen angulation marked on the ringadapter, optimal scanning planes might be determined prior to imaging.

For planar radiography, a cross-shaped grid of radiopaque (e.g. lead oraluminum) dots at 1 cm intervals interposed by 5 cm spaced dashes (FIG.15E) would minimize the imaging area obscured by overlying radiopacity.The minute opacities could be reversibly affixed by clear tape to anunderlying marked adhesive fabric similar to that illustrated in FIG.15C. Alternatively, in FIG. 15F similarly spaced radiopaque dots anddashes could be dispensed reversibly affixed to a role of medical gradeadhesive tape with corresponding markings. Any length of this duallymarked taped could be applied to the patient to include a single dot asa point localizer.

In a planar localizer grid/phantom 700, 1 cm spaced horizontal andvertical tubes form a graph paper-like lattice as illustrated in FIG.16A. Tubes at 5 cm intervals (29) would have larger luminal diameters(e.g. 3 mm) than the others (e.g. 2 mm). Central vertical 730 andhorizontal 731 tubes would have a smaller diameter (e.g. 1 mm).Overlying the lattice at a 45 degree angle is a slice indicator tube732. Depending on the distance from the horizontal or vertical axesrespectively, axial or sagittal cross sections through the grid/phantom(GP) would demonstrate the slice indicator tube 732 uniquely positionedas it overlies a row of 1 cm spaced tubes. FIG. 16B illustrates arepresentative axial slice obtained 6 ½ cm above the horizontal axis.Note that the cross section of the slice indicator is positioned aboveand midway between the sixth and seventh tubes to the right of thesectioned vertical axis 730. Additionally, the thickness (t) of theimage section can be readily determined as it equals the cross-sectionalwidth (w) of the indicator minus the square root of 2 times the diameter(d) of the indicator lumen,(t=w−V2″ d).

The GP may be reversibly affixed to an adhesive/plastic sheet with acorresponding graph paper-like grid for skin marking and to serve as asterile interface between the patient and GP. Perforations 733 may beplaced in the sheet as shown in FIG. 16A to allow ready separation of across-like ruled adhesive fabric (similar to that illustrated in FIG.15C), from the remaining plastic sheet after imaging and removal of theGP.

The square GP should have outer dimensions equal to a multiple of 10 cm(e.g. 30 cm as illustrated) to allow for simple computation if GPs areplaced side to side for expanded surface coverage. Adapters could beprovided to ensure secure and precise positioned of adjacent GPs eitherin plane or at right angles to each other. The GPs can be flexible orrigid in construction and be utilized with or without skin adhesion andmarking.

Tubes may be filled uniformly or with a variety of known solutionshaving different imaging properties to serve as multipurpose references.For the latter, the 5 cm spaced tubes and slice indicator may be filledwith the same optimized solution as previously described, while each setof 4 intervening tubes could be filled with different solutions insimilar sequence. In this fashion, identical series of 5 referencesolutions would repeat every 5 cm, allowing intraslice signalhomogeneity to be assessed as well. If 9 rather than 5 differentsolutions are desired, sequences could instead be repeated every 10 cm.For MRI, the central tubes may also be surrounded by an oil/lipid withina larger lumen tube to serve as both a lipid signal reference and allowfor measurement of the fat/water spatial chemical shift. Furthermore, ifthe GP tubing is surrounded by a perflurocarbon or other substancewithout magnetic susceptibility, MR imaging could be improved byreducing skin/air susceptibility artifact and dampening motion. The GPmay also be incorporated into a variety of nonmodality specific pads(including the ubiquitous scanner table pad(s)), binders, compressionplates, biopsy grids and assorted stereotaxic devices.

Two additional variations are now described, potentially replacing thesomewhat complex cross design (FIGS. 15A-15F) with an extension of thebasic point localizer (FIGS. 14A-14I) or modification of the planarphantom/localizer (FIGS. 16A-16B). These changes may further simplifyand unify the proposed marking system.

In the first instance, rather than packaging the ring localizers in asheet as illustrated in FIG. 14I, they could be packaged in a strip orroll 800, regularly spaced at 5 cm or other intervals (FIG. 17). Thestrip 800 with attached ring and/or cross localizers could then serve asa linear reference of any desired length. By placing two stripsorthogonally, a cross-shaped grid is created. Individual rings can beremoved from the strip or rotated to customize the grid as desired (FIG.18).

In the second instance, by slightly modifying the square designillustrated in FIGS. 16A-16B, an elongated rectilinear or crossconfiguration (FIG. 17A) is achieved consisting of linearly arrangedsquares extending vertically and/or horizontally from the centralsquare. One tube in each of these squares will have a larger diameterthan the other similarly oriented tubes as determined by the square'sdistance from the isocenter. For example, the square centered 10 cmabove the isocenter would have its first tube situated to the right ofmidline given an increased diameter and the square centered 20 cm abovethe isocenter would have its second tube to the right of midline givenan increased diameter and so on.

Cross sectional distance from isocenter would be read by adding thedistance determined by each square's diagonally oriented slice indicatorto 10 times the numberline position of the largest diameter tube. FIG.8B illustrates the cross sectional appearance of an axial sectionobtained 12½ cm. above isocenter. By adding 2½ (the slice indicatorposition) to 10 times 1 (the tube with largest diameter), distance isreadily determined.

Alternatively, the caliber of all tubes could be kept constant andinstead an additional diagonal indicator tube passing through isocenteradded for each elongated axis (vertical with slope of 10 and horizontalwith slope of 1/10). Cross-sectional distance from isocenter would thenbe determined by looking at the position of both the additional andoriginal diagonal indicator tubes in reference to the crosssectionally-created number line.

It should also be noted that localizer grids similar to thoseillustrated in FIGS. 16A-16B and 18 could be constructed of barium (orother high x-ray attenuative material) impregnated sheets rather thantubes if computed tomography is the primary imaging modality desired andphantom attenuation values are not needed. This would significantlyreduce the cost of the grid, allowing disposability and retaining 1:1compatibility with the multifunctional tube filled grid/phantom.

Flexible Phased Array Surface Coil With Integrated Multimodality,Multifunctional Spatial Reference And Skin/Surface Marking System.

It should be further noted that applications consistent with the presentinvention may be modified to include a sheath for and inclusion of aflexible array MRI surface coil. Positioned vertically, this devicecould be closely applied to the entire cervical, thoracic, andlumbar-sacral spine. Additionally, the quantity of tubes which need tobe filled in the planar configuration to uniquely denote cross-sectionalpositioning, has been substantially reduced from the originalembodiment.

Phased array surface coils significantly increase signal to noise in MRIand are commonly employed for spine imaging. Currently, such spine coilsare rigid and planar in configuration. As such, patients can only beeffectively scanned in the supine position, lying with the back againstthe coil. This results in signal drop-off in regions where thespine/back is not in close proximity to the planar coil, particularlythe lumbar and cervical lordotic regions. The invention, describedherein, would reduce the signal drop-off and allow patients to bescanned in any position. The prone position, for example, wouldfacilitate interventional spine procedures that could not be performedwith the patient supine. Patients could also be more readily scanned inflexion or extension; or with traction or compression devices. Currentsurface coils also lack an integrated spatial reference and skin markingsystem. Inclusion of the proposed spatial reference and skin markingsystem would facilitate multi-modality image fusion and registration aswell as the performance of diagnostic or therapeutic spine procedures,such as biopsies, vertebroplasty, or XRT.

A grid-localizer would be adhered to the patient's spine. Tubing wouldbe filled with a MRI readily-visible solution such as water doped withCuSO4. The grid itself would typically be 10 cm wide and 70-90 cm inlength to cover the entire spine. An attached clear plastic sheath wouldallow introduction of a flexible array coil such as illustrated in FIG.9B.

The configuration of tubing would allow unambiguous determination of theMRI scan plane (axial or sagittal) in reference to the patient'sback/skin surface. The number of thin caliber tubes could denote thedistance from (0,0) in multiple of 10 cm as illustrated in FIG. 9B(those to the right or superior would be positive; those appearing tothe left or inferior would denote negative distances). Alternatively, asillustrated in FIGS. 9C-9D the integer distance in centimeters from asingle thin tube to the central tube could be multiplied by ten todenote distance from (0,0). Thus, 30 cm could be denoted by a singlethin tube 3 cm from the central tube rather than by 3 thin tubes as inFIG. 9B. As illustrated in FIGS. 9C, 9D, an axial slice taken 8 cmsuperior to (0,0), would reveal the cross sectional tubes illustrated in6 d. The thin tube being 1 cm to the right of the central tube woulddenote a vertical distance of 10 cm. The diagonal oriented tube incross-section, being 2 cm to the left of the central tube, would denotea vertical distance of −2 cm. Thus, the axial plane of section would be10−2=8 cm above (0,0).

Using the described reference/marking system affixed to the patient'sback, a diagnostic or therapeutic procedure could be performed underdirect MR guidance. Alternatively with a corresponding radiopaque gridaffixed to patient's back, the patient could be taken out of MRI scannerand have the procedure done with CT or fluoroscopic guidance. In eithercase, procedures could be performed by hand or with a robotic arm.

Algorithms for identifying and characterizing discs and vertebrae. Afast rule-based spine contour extraction method has been developed. Itconsists of the following steps: (1) locating inter-vertebral disclocations; (2) finding the inter-vertebral contour using a deformablecontour model; and (3) locating the vertebral boundary and the spinecontour. This method enables automated scan prescriptions, real-timelesion detection, and examination tailoring.

Recent advances in MRI to include the clinical implementation of phasedarray-coils and parallel sensitivity encoded imaging offer the potentialfor time and cost effective non-invasive holistic screening and detailedassessment of neuro-axis pathology, to include stroke and back pain—bothleading causes of disability in the U.S. However, optimal patientevaluation requires individually optimized MRI sequencing, which in turnrequires real-time analysis of increasingly complex and multi-parametricMR data. The development and integration of an automated systememulating/approximating detailed expert analysis while the patient isstill in the magnet would significantly improve diagnostic imaging andmedical care. Millions of MRI scans are performed each year,approximately 65% dedicated to the evaluation of the brain and spine.Software to synergistically improve the prescription and analysis ofsuch scans has tremendous commercial potential. No such product iscurrently available and would be of great interest to both large medicalimaging companies engaged in computer assisted medical imagingdiagnosis.

Medical Applications—Detection and Analysis of Brain Pathology with MRI(Acute Stroke, Intracranial Aneurysms). At UC Medical Center, Talairachreferenced axial diffusion-weighted images (DWI), whether prescribed bya technologist or a computer, are currently obtained following theinitial roll and yaw corrected sagittal T2 sequence. If computer imageanalysis of the initial DWI sequence suggests regions of acuteinfarction, the basic brain protocol would be streamlined and modifiedto include MR angiography and perfusion sequencing. This wouldrespectively permit evaluation of the underlying vascular lesion and thedetection of potential perfusion/diffusion mismatches directing emergentneuro-vascular intervention. Stroke is the leading cause of disabilityin this country. Because the time to emergent therapy strongly inverselycorrelates with morbidity and mortality, the development andimplementation of the proposed computer algorithms could significantlyimprove patient outcome.

In conjunction with the Mayo Clinic, researchers at UC Medical Centerare currently studying a large population of patients at risk forintra-cranial aneurysms using MR angiography. One of the investigators(Dr. Weiss) has developed and implemented co-registered white and blackblood MR angiography sequences which uniquely facilitates computer-aideddiagnosis and analysis of potential aneurysms in this population. In theproposed work, such computer algorithms will be developed and theirsensitivity will be compared against the expert standard (3 independenteuroradiologists' assessments already in place). If computer imageanalysis of such initial MRA screening sequences reveals a potentialaneurysm, dedicated phase-contrast images of the putative aneurysm couldbe iteratively prescribed to better characterize the lesion and assessflow characteristics.

Using computer flow modeling and other engineering analysis, theinvestigators plan to better stratify an individual aneurysm's risk forrupture, This could lead to more optimized patient management as themajority of brain aneurysms do not rupture and therapeutic intervention(coiling or clipping) carries morbidity and mortality risks. Tobaccosmoking significantly increases the incidence ischemic brain disease aswell as aneurysms and their rupture leading to catastrophic stroke.

Detection and Analysis of Spine Pathology with MRI (Fractures, DiscHerniations). Spine pathology is another leading cause of disability inthis country. The proposed research will improve detection andassessment of disco-vertebral degeneration, osteoporotic and pathologiccompression fractures-all potential underlying causes of ubiquitousback/neck pain in this country.

Using advanced MR imaging techniques, the entire spinal axis can beinterrogated in the sagittal plane in less than a minute. With thisscreening data, the vertebral bodies and inter-vertebral discs can beidentified and subsequently analyzed with the software proposed fordevelopment. Based on this initial assessment, regions of suspectedpathology to include vertebral fractures and disc hemations, could befurther interrogated with more dedicated computer driven prescriptionsto confirm and better characterize pathology. If for example, a fractureis identified, additional multiparametric sequencing through theinvolved vertebrae would be obtained to determine whether the fracturewas related to osteoporosis or underlying malignancy.

In conjunction, with the aforementioned software to iterativelyprescribe and analyze brain MRI, the entire neuro-axis can beeffectively screened and lesions characterized in a singletime-efficient scan session. Currently, such an examination isprohibitively lengthy and requires several imaging sessions if lesionswere to be optimally characterized. Image analysis development for thisMRI project should be synergistic with that done for the X-rayevaluation of vertebrae in the following section.

Automated Spine MRI for Rapid Osteoporosis Screening. With the spinelabeled and imaged, further analysis is then enabled for diagnosingconditions of the spine. Novel MRI technique provides efficientscreening and iterative assessment of patients at risk for osteoporoticspine fractures. In particular, refinement of the above-describedAutomated Spine Survey Iterative Scan Technique (ASSIST) to optimizesub-minute morphologic screening of entire spine with MRI; (2) tocombine technique with investigational 3-point Dixon methodology toprovide quantitative assessment of vertebral marrow fat fraction (F %)and cancellous bone-induced intravoxel spin dephasing rate (R2*); and(3) to perform multi-variate analysis to model vertebral fracture riskas approximated by #1, with F %, R2*, and spinal dual-energy x-rayabsorptiometric (DEXA) bane mineral density (BMD).

Osteoporosis is a disease characterized by low bone mineral density andabnormal bone microarchitecture. Currently, it affects about 30% ofpost-menopausal women, with more than 50% at risk. With our populationrapidly aging, the prevalence of osteoporosis continues to rise. Asosteoporotic-related fractures result in major morbidity, health careexpenditures, and mortality in the elderly, this proposal addresses theDDF's desire to promote research in Aging-Geriatrics. Moreover, byapplying cutting-edge investigational technology to this criticalhealth-care problem, the study fulfills Translational ResearchInitiative goals as well.

The traditional criterion for assessing fracture risk is bone mineraldensity (BMD) as may be measured by single-photon absorptiometry (SPA),quantitative computed tomography (QCT), single-energy x-rayabsorptiometry (SXA), and most commonly dual-energy x-ray absorptiometry(DEXA). Unfortunately, while negatively correlated with fracture risk,BMD by itself remains an unsatisfactory predictor. Consequently,investigational work has increasingly focused on ultrasound and MRI. Thelatter technique has the unique potential to quantify fractures, whichare highly correlated with subsequent risk of fracture; differentiatebetween osteoporosis and other underlying pathology, such as metastases;and target therapy such as vertebroplasty. MRI researchers have alsodemonstrated improved fracture risk prediction by combining DEXAmeasurements with Dixon sequence derived F % (positively correlated) andR2* (negatively correlated). Unfortunately, MRI of the spine has beentoo time intensive and costly to justify as an osteoporosis-screeninginstrument.

To rectify this important shortcoming, integration is made of the3-point Dixon technique with our novel automated sub-minutesub-millimeter resolution total spine screen. This should afford rapidhigh-resolution morphometric assessment, as well as, the separation andquantification of fat, water, and R2*. We plan to test this methodologyon 50 post-menopausal women who have been referred for a DEXA scan.

In particular, a novel MRI technique improves current screening,assessment, and surveillance of the elderly at risk for osteoporoticspine fractures. As osteoporotic fractures result in major morbidity,health care expenditures, and mortality in the geriatric population,this proposal directly addresses the Dean's Discovery Fund's desire topromote research in Aging/Geriatrics. Moreover, by applying cutting-edgeinvestigational technology to this critical health-care problem, thestudy fulfills Translational Research Initiative goals as well.

Osteoporosis and related fractures are a leading cause of morbidity,disability, decreased quality of life and mortality in the aged. (2-4)The wide range of therapeutic options available for prevention andtreatment require effective screening, assessment, and monitoring ofgeriatric patients at risk for osteoporotic fractures. Conventionalmeasurements including bone mineral density (BMD) analysis are imperfectpredictors of fractures. (4) MRI-derived parameters hold promise forimproved risk prediction and fracture evaluation. (5) Unfortunately, MRIhas been too time intensive and costly to justify as anosteoporosis-screening instrument. To rectify this importantshortcoming, we propose refinement and integration of MRI derivedparameters of bone quality with our novel rapid high-resolution totalspine screen (1) The long term goal is to promote geriatric patient careby providing improved risk assessment, identification andcharacterization of fractures.

The central hypothesis is that our computer automated MRI technique willefficiently screen and assess elderly post-menopausal women at risk forosteoporotic spine fractures. More specifically, our multi-parametricapproach will 1) improve fracture risk prediction and 2) accuratelyidentify and characterize existing fractures. The following specificaims will be pursued to test this hypothesis:

Improve vertebral fracture risk prediction: MRI derived measurements ofvertebral morphology and bone quality (fat fraction, F %; transverserelaxation rate, R2*) will be calculated for each vertebra. Theseparameters will be analyzed in conjunction with standard dual-energyx-ray absorptiometric (DXA) to develop a model for prediction ofvertebral fracture risk.

Accurately identify and characterize existing vertebral fractures: Ournovel MRI Automated Spine Survey Iterative Scan Technique (ASSIST) willbe adapted to provide automated morphologic assessment of vertebrae anddetect vertebral fracture deformities. This functionality will becompared to lateral thoracolumbar x-ray, which currently serves as theclinical standard.

Osteoporosis is an important geriatric health issue and poses a mostserious public health problem. With life expectancies increasing, thefinancial and human costs associated with osteoprotic fractures willmultiply exponentially throughout the world. Vertebral fractures arestrongly correlated with age (mean 65 years) but even more so withmenopause. In the United States, one out of two women and one in fourmen over age 50 will have an osteoporosis-related fracture.

Osteoporosis is a metabolic disease characterized by low bone mineraldensity and abnormal bone microarchitecture increasing fracture risk.The traditional criterion for assessing fracture risk is bone mineraldensity (BMD) as may be measured by single-photon absorptiometry,quantitative computed tomography, single-energy x-ray absorptiometry, ormost commonly dual-energy x-ray absorptiometry (DXA). Unfortunately,while negatively correlated with fracture risk, BMD by itself is not aperfect predictor.

Fractures are the ultimate manifestation of lost bone structuralintegrity. One fractured vertebra increases the risk of subsequentvertebral fracture 5-fold. Consequently, low resolution morphometricx-ray absorptiometry and/or more precise high resolution conventionalthoracolumbar spine x-rays are often ordered to supplement BMD measures.Vertebral fractures are commonly assessed on x-rays semiquantitativelyand reported using Genant's 0-3 grading scale with grade 1 correspondingto a fracture deformity of 20-25%. More mild deformities are typicallynot scored but are also somewhat associated with lower BMD and increasedfracture susceptibility.

Conventional radiography, however, has several shortcomings in thedetection of vertebral fractures. Different technical parameters in theacquisition of lateral spine radiographs influence vertebral dimensionmeasurements, thus degrading reproducibility, especially in scolioticpatients. Vertebral body outlines are more difficult to visualize onx-ray in the population most at risk for osteoporotic fracture due totheir reduced BMD. Radiographs also have limited ability to assessfracture chronicity, etiology, or potential effectiveness of targetedintervention to include vertebroplasty or kyphoplasty. Moreover,ionizing radiation from serial radiographic examinations must be takeninto account, especially when considering clinical trials typicallyrequiring numerous exposures.

Consequently, investigations have increasingly focused on ultrasound andMRI. MRI has the unique potential to simultaneously quantify fractures;differentiate between osteoporosis and other underlying pathology, suchas metastases; and appropriately target therapy such as vertebroplasty.Additionally, spinal MRI affords direct visualization of theintervertebral discs, spinal canal, bone marrow, and neural tissue. MRIcan accurately quantify vertebral morphology. Cyteval and colleagueshave recently demonstrated the accuracy and reproducibility of MRI forthe determination of vertebral body dimensions. They also found that thesagittal midline area was highly correlated with whole vertebral bodyvolume and that each vertebra was proportional to other vertebrae in thesame individual.

MRI can also provide bone quality measurements related to osteoporosis.MRI researchers have demonstrated improved fracture risk prediction bycombining DXA measurements with Dixon sequence derived fat percentage—F%(positively correlated) and transverse relaxation rate—R2* (negativelycorrelated). When trabeculae are not aligned with the magnetic field,susceptibility differences at the interface between trabecular bone andbone marrow increase R2*. Consequently, R2* measurements reflect bothtrabecular bone structure and orientation.

The Dixon technique exploits the resonant frequency differences betweenfat and water to separate the water signal intensity from the fat signalintensity. This frequency difference is measured as a phase differencein the acquired data. Acquisition of three separate measurements orDixon echoes allows generation of a water image, a fat image, and amagnetic susceptibility map from which F % and R2* can be derived. (6)

To date, while promising, MRI examinations have been too time intensiveand costly to justify for osteoporosis-screening. To rectify thisimportant shortcoming, we propose integration of the three-point Dixontechnique with our novel automated sub-minute sub-millimeter resolutiontotal spine screen. This should afford rapid high-resolution assessmentof both vertebral morphometry and bone quality.

Rapid Osteoporosis Screening: Sagittal FGRE (TR 58; TE 2.1; 30° flip; 7slices; 4 mm skip 1 mm; 35 cm FOV×2=70 cm) with contiguous superior andinferior stations. The imaging parameters have been selected toemphasize contrast between vertebral discs and bodies with full coveragefrom the cervical spine through the sacrum in 42 seconds.

Three-Point Dixon Technique: Sagittal FSE Dixon (7 slices; 4 mm skip 1mm; 44 cm FOV) covering T4-S1 and prescribed using the superior ASSISTstation as localizer. The Dixon technique exploits molecular resonantfrequency differences between fat and water to produce high resolutionfat, water, and transverse relaxation rate (R2*) images.

While the present invention has been illustrated by description ofseveral embodiments and while the illustrative embodiments have beendescribed in considerable detail, it is not the intention of theapplicant to restrict or in any way limit the scope of the appendedclaims to such detail. Additional advantages and modifications mayreadily appear to those skilled in the art.

1. An apparatus for identifying and labeling spinal structures in a medical diagnostic image of a patient, comprising: a memory configured to receive the medical diagnostic images; a program stored in the memory and operatively configured to detect a plurality of voxels in the image as candidate spinal structures, to apply at least one spinal structure constraint to identify a subset of the plurality of voxels as a series of spinal structures, and to label the series of spinal structures as a selected specified one of a cervical, thoracic, lumbar vertebral structures; and a processor in communication with the memory to perform the program.
 2. The apparatus of claim 1, wherein the program is further operatively configured to identify a selected seed vertebral structure and to identify adjacent vertebral structures by locating a longest chain of voxels and analyzing spacing and quantity of voxels in the longest chain.
 3. The apparatus of claim 1, wherein the program is further configured to define putative spine structures by defining a search region, applying intensity thresholds, applying additional disc constraints, and identifying the longest chains.
 4. The apparatus of claim 3, wherein the program is further configured to combine data and then search along a reconstructed path neighborhood for local maxima.
 5. The apparatus of claim 4, wherein the program is further configured to make a determination whether twenty three spinal discs have been selected, and if not to search for an additional discs based on estimated interdisc distance for each level.
 6. The apparatus of claim 4, wherein the program is further configured to search for an additional disc by extending a line from the longest chain and analyze for an additional disc.
 7. The apparatus of claim 4, wherein the program is further configured to search for additional discs by extending the search line, drawing additional parallel lines to the extended line and analyze for additional discs.
 8. The apparatus of claim 4, wherein the program is further configured to search for an additional disc by analyzing an elongate space between adjacent discs and analyze for an additional disc by adjusting a search constraint.
 9. The apparatus of claim 4, wherein the program is further configured to apply optimized Gaussian filters to the search part.
 10. The apparatus of claim 4, wherein the program is further configured to search for auto-prescribed additional imaging planes and sequences.
 11. The apparatus of claim 1, wherein the program is further configured to analyze a selected spinal structure to diagnose osteoporosis.
 12. A method for performing a medical diagnostic imaging scan of a patient, comprising: placing a longitudinally unique opaque spinal coil on external to a spine of a patient; performing a scout scan; identifying and labeling on diagnostic scans each vertebral body of the spin; autoprescribing a portion proximate to a vertebral body for a detailed scan; identifying a unique longitudinal position of the spinal coil proximate to a surgical site contained within the autoprescribed portion; and inserting a therapeutic instrument localized by the spinal coil to the surgical site. 